IOWA Wild

GP: 28 | W: 12 | L: 14 | OTL: 2 | P: 26
GF: 166 | GA: 212 | PP%: 18.37% | PK%: 61.29%
DG: Martin Gagnon | Morale : 94 | Moyenne d'Équipe : 61
Prochain matchs #365 vs VICTORIAVILLE Tigres
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Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur #C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SP
1Jason Dickinson0X100.007441736880828067757064716654517779700
2Tyler Motte0X100.008735756669808765596465726556525779700
3Drake Caggiula0X100.008444717066826869626869666957524298690
4Zach Sanford0X100.006441736688778065696663636454516590680
5Iiro Pakarinen0X100.007241826778747559305963686955534298660
6Peter Holland0XX100.005689607081505070706565506561537098610
7Matej Stransky (R)0X100.005338706980505761305259515760507198590
8Yakov Trenin0X100.005589646781505067705858565850504490590
9Owen Tippett (R)0X100.005540826676722956305656606450508890580
10Stanislav Galiev0X100.004935787074474060305254565562516390560
11Joseph Cramarossa0X100.005089466373505063505353505352515690550
12Tanner Kaspick (R)0X100.005189675774505057705454505450504495550
13Mark Alt0X100.005935676487505164304944505451505890560
14Matt Bartkowski0X100.005435626177485161304843545460583895550
15Konrad Abeltshauser (R)0X100.004935786088454049303428554860557198500
Rayé
MOYENNE D'ÉQUIPE100.00615270667860576249575658605552599260
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Alex Stalock100.00797276747877797877787359693795680
Rayé
MOYENNE D'ÉQUIPE100.0079727674787779787778735969379568
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Benoit Groulx67676767727268CAN52375,000$


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Owen TippettIOWA Wild (MIN)RW2845752-116099542637916417.11%6350217.966062235000002060.00%2500072.0700000510
2Zach SanfordIOWA Wild (MIN)LW282521461414033352216714611.31%1835912.8401105000012074.07%2700032.5600000132
3Joseph CramarossaIOWA Wild (MIN)C28202545151001946212591329.43%2535012.5200045000002069.11%39500012.5700000123
4Yakov TreninIOWA Wild (MIN)C2835035-174054281724110720.35%5333812.1000021000002176.40%32200042.0700000143
5Stanislav GalievIOWA Wild (MIN)RW2825833-262072322378217310.55%4742415.172021632000001057.14%2100041.5500000312
6Mark AltIOWA Wild (MIN)D2892231-9100521269203313.04%4139814.240114600002200.00%000001.5500000001
7Drake CaggiulaIOWA Wild (MIN)C1101-1207551320.00%12525.9310124000000045.00%2000000.7700000000
8Matt BartkowskiIOWA Wild (MIN)D1000-100201000.00%12424.230000400001000.00%000000.0000000000
9Jason DickinsonIOWA Wild (MIN)C1000000043120.00%22929.0200015000020055.56%2700000.0000000000
10Peter HollandIOWA Wild (MIN)C/LW1000020114010.00%02020.0300025000000033.33%300000.0000000000
11Iiro PakarinenIOWA Wild (MIN)RW1000000044120.00%01515.6200015000000050.00%200000.0000000000
12Konrad AbeltshauserIOWA Wild (MIN)D1000000000010.00%02424.120000500001000.00%000000.0000000000
13Matej StranskyIOWA Wild (MIN)RW1000-100001010.00%12020.72000050000000100.00%100000.0000000000
14Tyler MotteIOWA Wild (MIN)LW1000000524220.00%12727.6500015000020045.45%1100000.0000000000
15Tanner KaspickIOWA Wild (MIN)C1000000011000.00%01414.5700000000000042.86%700000.0000000000
Stats d'équipe Total ou en Moyenne17716083243-37500344224119735376713.37%253257614.5692115512600001411169.80%861000191.8900000111111
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien Nom de l'ÉquipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Alex StalockIOWA Wild (MIN)10010.9231.9761202260100.000010000
Stats d'équipe Total ou en Moyenne10010.9231.9761202260100.000010000


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Alex StalockIOWA Wild (MIN)G321987-07-28No90 Kg183 CMNoNoNo4Sans RestrictionPro & Farm800,000$0$0$NoLien
Drake CaggiulaIOWA Wild (MIN)C271992-01-09 14:02:10No80 Kg178 CMNoNoNo2Avec RestrictionPro & Farm1,500,000$0$0$NoLien
Iiro PakarinenIOWA Wild (MIN)RW281991-08-25No96 Kg185 CMNoNoNo3Sans RestrictionPro & Farm750,000$0$0$NoLien
Jason DickinsonIOWA Wild (MIN)C241995-07-04No91 Kg188 CMNoNoNo4Avec RestrictionPro & Farm900,000$0$0$NoLien
Joseph CramarossaIOWA Wild (MIN)C261992-10-26No87 Kg183 CMNoNoNo4Avec RestrictionPro & Farm750,000$0$0$NoLien
Konrad AbeltshauserIOWA Wild (MIN)D261992-09-02Yes102 Kg196 CMNoNoNo4Avec RestrictionPro & Farm1,500,000$0$0$No
Mark AltIOWA Wild (MIN)D271991-10-18No91 Kg193 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$NoLien
Matej StranskyIOWA Wild (MIN)RW261993-07-11Yes95 Kg191 CMNoNoNo5Avec RestrictionPro & Farm750,000$0$0$No
Matt BartkowskiIOWA Wild (MIN)D311988-06-04No90 Kg185 CMNoNoNo6Sans RestrictionPro & Farm750,000$0$0$NoLien
Owen TippettIOWA Wild (MIN)RW201999-02-16Yes91 Kg185 CMNoNoNo5Avec RestrictionPro & Farm750,000$0$0$NoLien
Peter HollandIOWA Wild (MIN)C/LW281991-01-14No93 Kg188 CMNoNoNo5Sans RestrictionPro & Farm750,000$0$0$NoLien
Stanislav GalievIOWA Wild (MIN)RW271992-01-17No90 Kg188 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$No
Tanner KaspickIOWA Wild (MIN)C211998-01-28Yes91 Kg183 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Tyler MotteIOWA Wild (MIN)LW241995-03-10No87 Kg178 CMNoNoNo5Avec RestrictionPro & Farm800,000$0$0$NoLien
Yakov TreninIOWA Wild (MIN)C221997-01-13No91 Kg188 CMNoNoNo5Avec RestrictionPro & Farm750,000$0$0$NoLien
Zach SanfordIOWA Wild (MIN)LW241994-11-09No94 Kg193 CMNoNoNo6Avec RestrictionPro & Farm1,000,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1625.8191 Kg185 CM4.38875,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tyler MotteJason DickinsonIiro Pakarinen31122
2Zach SanfordDrake CaggiulaMatej Stransky26122
3Tyler MottePeter HollandOwen Tippett23122
4Jason DickinsonYakov TreninStanislav Galiev20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark AltMatt Bartkowski31122
2Konrad AbeltshauserPeter Holland26122
3Mark AltMatt Bartkowski23122
4Konrad AbeltshauserDrake Caggiula20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tyler MotteJason DickinsonIiro Pakarinen55122
2Zach SanfordDrake CaggiulaMatej Stransky45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark AltMatt Bartkowski55122
2Konrad AbeltshauserPeter Holland45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Tyler MotteJason Dickinson55122
2Drake CaggiulaZach Sanford45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark AltMatt Bartkowski55122
2Konrad Abeltshauser45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Tyler Motte55122Mark AltMatt Bartkowski55122
2Jason Dickinson45122Konrad Abeltshauser45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Tyler MotteJason Dickinson55122
2Drake CaggiulaZach Sanford45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark AltMatt Bartkowski55122
2Konrad Abeltshauser45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tyler MotteJason DickinsonIiro PakarinenMark AltMatt Bartkowski
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tyler MotteJason DickinsonIiro PakarinenMark AltMatt Bartkowski
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Tanner Kaspick, Joseph Cramarossa, Yakov TreninTanner Kaspick, Joseph CramarossaYakov Trenin
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mark Alt, Matt Bartkowski, Konrad AbeltshauserMark AltMatt Bartkowski, Konrad Abeltshauser
Tirs de Pénalité
Tyler Motte, Jason Dickinson, Drake Caggiula, Zach Sanford, Iiro Pakarinen
Gardien
#1 : Alex Stalock, #2 :
Lignes d'Attaque Perso. en Prol.
Tyler Motte, Jason Dickinson, Drake Caggiula, Zach Sanford, Iiro Pakarinen, Peter Holland, Peter Holland, Matej Stransky, Yakov Trenin, Owen Tippett, Stanislav Galiev
Lignes de Défense Perso. en Prol.
Mark Alt, Matt Bartkowski, Konrad Abeltshauser, ,


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
Total28121400200166212-4613580000073110-3715760020093102-9260.4641662574230092492501517484517515112673166845249918.37%311261.29%037673850.95%20853738.73%30461849.19%689540698148295150
_Since Last GM Reset28121400200166212-4613580000073110-3715760020093102-9260.4641662574230092492501517484517515112673166845249918.37%311261.29%037673850.95%20853738.73%30461849.19%689540698148295150
_Vs Conference22101100100138165-271055000007077-71256001006888-20210.477138209347009249250124448451751519702506034039923.08%271062.96%037673850.95%20853738.73%30461849.19%689540698148295150
_Vs Division1146001006988-195140000041374632001002851-2390.4096910917800924925066048451751515231352818118211.11%14750.00%037673850.95%20853738.73%30461849.19%689540698148295150

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2826OTL1166257423151712673166845200
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2812140200166212
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
1358000073110
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1576020093102
Derniers 10 Matchs
WLOTWOTL SOWSOL
350200
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
49918.37%311261.29%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
48451751519249250
Mises en Jeu
Gagnées en Zone OffensiveTotal en Zone Offensive% Gagnées en Zone Offensive Gagnées en Zone DéfensiveTotal en Zone Défensive% Gagnées en Zone DéfensiveGagnées en Zone NeutreTotal en Zone Neutre% Gagnées en Zone Neutre
37673850.95%20853738.73%30461849.19%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
689540698148295150


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
1 - 2019-07-306CORNWALL Aces6IOWA Wild10WSommaire du Match
2 - 2019-07-3125IOWA Wild11STOCKTON Flames3WSommaire du Match
3 - 2019-08-0136BELLEVILLE Senators10IOWA Wild4LSommaire du Match
5 - 2019-08-0355MONT-LAURIER Sommet11IOWA Wild2LSommaire du Match
6 - 2019-08-0465IOWA Wild11SYRACUSE Crunch4WSommaire du Match
7 - 2019-08-0568IOWA Wild1BELLEVILLE Senators9LSommaire du Match
9 - 2019-08-0787IOWA Wild3LEHIGH VALLEY Phantoms11LSommaire du Match
10 - 2019-08-0897MONT-LAURIER Sommet9IOWA Wild1LSommaire du Match
11 - 2019-08-09107IOWA Wild14HOLLYWOOD Oscar5WSommaire du Match
12 - 2019-08-10122MANITOBA Moose10IOWA Wild1LSommaire du Match
14 - 2019-08-12142WILKIES-BARRIE Penguins3IOWA Wild13WSommaire du Match
15 - 2019-08-13149IOWA Wild10BROOKLYN Wolfpack3WSommaire du Match
17 - 2019-08-15168VICTORIAVILLE Tigres13IOWA Wild6LSommaire du Match
18 - 2019-08-16177IOWA Wild0PV Sharapovas12LR3Sommaire du Match
20 - 2019-08-18186CORNWALL Aces4IOWA Wild14WSommaire du Match
21 - 2019-08-19198IOWA Wild13CORNWALL Aces5WSommaire du Match
22 - 2019-08-20210IOWA Wild1TORONTO Marlies10LSommaire du Match
24 - 2019-08-22222IOWA Wild10HOLLYWOOD Oscar3WSommaire du Match
25 - 2019-08-23236COLORADO Eagles10IOWA Wild0LSommaire du Match
26 - 2019-08-24253LAVAL Rockets12IOWA Wild2LSommaire du Match
27 - 2019-08-25269HERSEY Bears11IOWA Wild1LSommaire du Match
28 - 2019-08-26283IOWA Wild10TUSCON Roadrunners5WSommaire du Match
29 - 2019-08-27295IOWA Wild1MONT-LAURIER Sommet13LSommaire du Match
30 - 2019-08-28300IOWA Wild5SAN DIEGO Gulls6LXSommaire du Match
31 - 2019-08-29314CORNWALL Aces5IOWA Wild11WSommaire du Match
32 - 2019-08-30325IOWA Wild2PV Sharapovas11LR3Sommaire du Match
33 - 2019-08-31336LEHIGH VALLEY Phantoms6IOWA Wild8WSommaire du Match
35 - 2019-09-02352IOWA Wild1MANITOBA Moose2LXSommaire du Match
36 - 2019-09-03365VICTORIAVILLE Tigres-IOWA Wild-
37 - 2019-09-04378UTICA Comets-IOWA Wild-
39 - 2019-09-06398IOWA Wild-CLEVELAND Monsters-
40 - 2019-09-07404TORONTO Marlies-IOWA Wild-
42 - 2019-09-09421IOWA Wild-HERSEY Bears-
43 - 2019-09-10431TORONTO Marlies-IOWA Wild-
45 - 2019-09-12449CLEVELAND Monsters-IOWA Wild-
46 - 2019-09-13463IOWA Wild-STOCKTON Flames-
47 - 2019-09-14475IOWA Wild-CORNWALL Aces-
48 - 2019-09-15487MANITOBA Moose-IOWA Wild-
49 - 2019-09-16499IOWA Wild-CLEVELAND Monsters-
50 - 2019-09-17513TUSCON Roadrunners-IOWA Wild-
52 - 2019-09-19530BRIDGEPORT Sound Tigers-IOWA Wild-
53 - 2019-09-20536IOWA Wild-MANITOBA Moose-
54 - 2019-09-21555BELLEVILLE Senators-IOWA Wild-
55 - 2019-09-22557IOWA Wild-CHICAGO Wolves-
58 - 2019-09-25578IOWA Wild-COLORADO Eagles-
59 - 2019-09-26587PV Sharapovas-IOWA Wild-
61 - 2019-09-28606WILKIES-BARRIE Penguins-IOWA Wild-
62 - 2019-09-29617IOWA Wild-LEHIGH VALLEY Phantoms-
65 - 2019-10-02633SAN DIEGO Gulls-IOWA Wild-
67 - 2019-10-04646IOWA Wild-BROOKLYN Wolfpack-
68 - 2019-10-05662ROCKFORD IceHogs-IOWA Wild-
70 - 2019-10-07680IOWA Wild-VICTORIAVILLE Tigres-
71 - 2019-10-08686MILWAUKEE Admirals-IOWA Wild-
73 - 2019-10-10701IOWA Wild-WILKIES-BARRIE Penguins-
74 - 2019-10-11712BROOKLYN Wolfpack-IOWA Wild-
75 - 2019-10-12730CHICAGO Wolves-IOWA Wild-
76 - 2019-10-13738IOWA Wild-MONT-LAURIER Sommet-
77 - 2019-10-14753IOWA Wild-WILKIES-BARRIE Penguins-
78 - 2019-10-15763IOWA Wild-BELLEVILLE Senators-
79 - 2019-10-16773LEHIGH VALLEY Phantoms-IOWA Wild-
81 - 2019-10-18791MONT-LAURIER Sommet-IOWA Wild-
83 - 2019-10-20808IOWA Wild-ROCKFORD IceHogs-
84 - 2019-10-21819STOCKTON Flames-IOWA Wild-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
85 - 2019-10-22834IOWA Wild-MILWAUKEE Admirals-
86 - 2019-10-23839IOWA Wild-SYRACUSE Crunch-
87 - 2019-10-24851STOCKTON Flames-IOWA Wild-
89 - 2019-10-26865PV Sharapovas-IOWA Wild-
90 - 2019-10-27881IOWA Wild-BRIDGEPORT Sound Tigers-
91 - 2019-10-28893IOWA Wild-LAVAL Rockets-
92 - 2019-10-29899SYRACUSE Crunch-IOWA Wild-
94 - 2019-10-31921PROVIDENCE Bruins-IOWA Wild-
96 - 2019-11-02932IOWA Wild-PROVIDENCE Bruins-
98 - 2019-11-04948SYRACUSE Crunch-IOWA Wild-
100 - 2019-11-06962IOWA Wild-UTICA Comets-
102 - 2019-11-08975HOLLYWOOD Oscar-IOWA Wild-
103 - 2019-11-09989HOLLYWOOD Oscar-IOWA Wild-
105 - 2019-11-111000IOWA Wild-VICTORIAVILLE Tigres-
106 - 2019-11-121012IOWA Wild-TORONTO Marlies-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
26 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
446,862$ 1,400,000$ 1,400,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 422,327$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 72 13,785$ 992,520$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
3228121400200166212-4613580000073110-3715760020093102-9261662574230092492501517484517515112673166845249918.37%311261.29%037673850.95%20853738.73%30461849.19%689540698148295150
Total Saison Régulière28121400200166212-4613580000073110-3715760020093102-9261662574230092492501517484517515112673166845249918.37%311261.29%037673850.95%20853738.73%30461849.19%689540698148295150